JOURNAL OF RESEARCH AND INNOVATION IN INFORMATION SYSTEMS http://seminar.utmspace.edu.my/myaisprint/ REVIEW ON “EXPECTANCY DISCONFIRMATION THEORY” (EDT) MODEL IN B2C E-COMMERCE
NAEIMEH ELKHANI1
[email protected]
ARYATI BT BAKRI2
[email protected]
Author(s) Contact Details:
1
University Technology Malaysia, Skudai, Johor Bahru, Malaysia
Abstract— this study focuses on a review of “Expectancy Disconfirmation Theory” (EDT) as a famous theory in measuring
customer’s satisfaction. In today’s competitive e-marketplace, e-businesses that determine an efficient strategic think
behind their e-commerce activities involve designing a qualified website and presenting good quality of products and
services will be more successful in attracting customer satisfaction. These points emphasize on the importance of attracting
customer’s satisfaction for the vita of e-businesses. That’s why measuring customer’s satisfaction by an empowerment tool
that has ability to cover and make relationship among all concepts that are explained above is imperative. “Expectancy
Disconfirmation Theory” (EDT) which is defined as an theory for measuring customer satisfaction from perceived quality
of products or services is reviewed in this research for measuring customers satisfaction. Evolution of “EDT” shown this
theory is able to measure quality of services and information which provided by B2C E-commerce from customer’s point of
view. Moreover, review on EDT measurement methods and their strengths and weaknesses in accuracy of the results shown
that Additive Difference Model (ADM) and Direct Effects Model (DEM) worked well across both standards involve
customer‘s expectation and desire. Between DEM and ADM methods, when managers need information about desires and
expectations DEM appears to be a good choice but it does not provide a distinct measure of the disconfirmation of
customer‘s expectation and desire. In versus ADM provide a distinct measure of the disconfirmation of customer‘s
expectation and desire. That’s why it is concerned by managerial issues.
Keywords – Customer Satisfaction; “Expectancy Disconfirmation Theory” (EDT)
1. INTRODUCTION
Nowadays, the online marketplace is rapidly growing and the businesses that tend to get benefit from emarketplace are expanding. In such competitive e-marketplace, those have more consider for attracting
customer’s satisfaction from different aspects of electronic commerce (e-commerce), for instance, the quality of
websites [1] and quality of offered products and services [2,3] on the websites, will possess more share in the emarketplace. That’s why organizations need to more considered on their customer satisfaction when they
involve with e-commerce. E-commerce plays a transaction role of an electronic medium between two or
multiple parties [4]. The kind of online transaction which an organization deals with its customers directly is
known business to customer (B2C).
In order to measure customer satisfaction in e-commerce, EDT is introduced as an important theory
which can measure customer satisfaction from perceived quality of products or services [5,6,7]. EDT has two
famous variables that are named (expectation or desire) and (experience or perceived performance). These
ISSN: 2289‐1358 P a g e | 1 JOURNAL OF RESEARCH AND INNOVATION IN INFORMATION SYSTEMS http://seminar.utmspace.edu.my/myaisprint/ variables are defined in two different time periods. (Expectation or desire) are related to the pre-purchase time
period that a customer has intial expectaion or desire about a specific performance such as quality of products
or services. (Experience or perceived performance) are related to the after-purchase time period that the
customer gets the experience after perceiving a real performance such as quality of a specific productor service.
The difference between initial expectation or desire and perceived experience or performance is known as
disinformation of expectation or desire [5,7,8].
The result of this difference, means disconfirmation of expectation or desire can be positive or
negative.When customer’s perceived performance about the quality of specific product or service is better than
customer’s expectation or desire,the positive disconfirmation will ocure.At the same way, when customers
perceives the performance worse than what they expected or desired about the quality of specific product or
service,the negative disconfirmation will emerge.According to [9] positive disconfirmation will lead to
customersatisfaction and negative disconfirmation means perceived performance of products or services
couldn’t attract customer satisfaction.
EDT has been applied by many researchers in different fields for better understanding of customer’s
expectations and requirements for attracting their satisfaction, such as marketing [5,10,11,12], tourism [13] ,
Psychology [14], information technology [8,15,16,17,18], repurchase behavior and retention [8,17,19,20] and
airline industry [21,22].
For evaluating customer satisfaction from quality of website, product and services, EDT according to
its natural competences can fulfill the responsibility of measuring customer satisfaction [5,7,19].
EDT has a psychological nature that can evaluate customer satisfaction from presented information on
the first level [23] and can evaluate customer satisfaction from presented quality of products and services in the
second and third level [5,6,7].
This study attempts to fulfill three objectives in this review involve:
•
Review on the evolution of EDT model and identify its capabilities in measuring customer satisfaction.
•
Review on different measurement methods of EDT.
•
Choosing an appropriate measurement method in EDT from E-commerce management’s point of view.
2. LITERATURE REVIEW
2.1 History of Cognitive Dissonance theory (CDT)
Expectancy Disconfirmation Theory (EDT) is conducted on the base of Cognitive Dissonance theory
(CDT) that is introduced in 1957 by Leon Festinger; therefore a literature of CDT is reviewed in this section
before review on the definition of EDT and its applications.
ISSN: 2289‐1358 P a g e | 2 JOURNAL OF RESEARCH AND INNOVATION IN INFORMATION SYSTEMS http://seminar.utmspace.edu.my/myaisprint/ Leon Festinger in 1957, proposed Cognitive Dissonance theory (CDT) that defines a dissonance
between cognition of something and its reality. Perceived dissonance causes to change a person’s idea about a
specific cognition [8]. This change has psychological reason, because feeling the dissonance between whatever a
person has taught about qualification of something and what he/she realize from actual performance is
unpleased and make discomfort in person’s mind and this uncomfortable feel encourage the person to change
her/his idea about cognition [24]. Festinger (1957) named this discomfort feel as dissonance.
A person for moderate the dissonance’s unpleasant feel, try to decrease the dissonance which is occurred
from the difference between two kinds of cognition as initial cognition of something and what is happened in
real world. Psychologically, a person attempts to enhance the significance of consonant cognition and reduce the
significance of dissonant cognitions in his/her mind, it means summation of consonant cognitions and
subtraction of dissonant cognitions [24].
On the other hand, normally persons resistant in versus change. They are willing to change their attitude
just when they have the least resistance to alter their idea. This kind of resistance is volunteer to change and can
reduce dissonance feel of cognition [24]. Reducing dissonance of cognitions by responsible, encourage the
persons to change their remaining idea about dissonance. For promoting a person’s satisfaction feel about
something or a performance, reducing the dissonance feel of cognition has significant importance [25].
In summary, CDT is a theory for matching the person’s expectation of something or a performance with
what he/she experience about this thing or this performance in real world. Dissonance between the expectation
and experience cause an unpleasant feel that according to human’s psychology, the persons demonstrate the
least resistance for reducing dissonance feel and are willing to align their expectation and experience, if the
difference or dissonance between their expectation and experience don’t be fundamental [26].
2.2 Evolution of EDT
Expectancy Disconfirmation Theory (EDT) is built on the base of (CDT) definition. (EDT) can measure
customer’s satisfaction from difference between customer’s expectation and experience in perceived products or
services [5,7,19]. Figure 2.1 is shown the first model of EDT which is proposed by [11].
Figure 2.1: First EDT model [5]
ISSN: 2289‐1358 P a g e | 3 JOURNAL OF RESEARCH AND INNOVATION IN INFORMATION SYSTEMS http://seminar.utmspace.edu.my/myaisprint/ This model is consists of four elements: expectations, perceived performance, Disconfirmation, and satisfaction
as following description:
Expectations define customer’s anticipates about performance of products and services [27]. EDT has
ability to define multiple manners of customers in purchase process. First, the customers have an initial
expectation according to their previous experience with using specific product or service. Expectation of this
kind of customers which repurchase from a specific business is more near to reality. Second, the new customers
that don’t have a first-hand experience about performance of product or services and for the first time they
purchase from a specific business. The initial expectation of this kind of customers is consist of feedbacks that
they receive from other customers, advertising or mass media [28].
Perceived performance indicates customer’s experience after using products or services that can be
better or worse than customer’s expectation [23]. Both kind of these customers who has first-hand experience or
don’t have first-hand experience will use purchased products or offered services for a while and can realize
actual quality of presented products or services by the business.
Disconfirmation is defined as the difference between customer’s initial expectation and observed actual
performance [8]. According to literature, disconfirmation is divided to three types consist of positive
disconfirmation, negative disconfirmation and simple disconfirmation.
When actual performance of specific product or services can’t meet customer’s expectation, negative
disconfirmation will occur and leads to customer’s dissatisfaction. Positive disconfirmation will lead to
customer’s satisfaction, if perceived performance of specific product or services are able to exceed customer’s
satisfaction. Finally, when there isn’t any difference between customer’s expectation and actual performance of
specific product or services, means perceived performance is equal with expectation and simple confirmation is
occurred [5,12]. There is some arguing in literature in definition of simple confirmation. While some
researchers believe satisfaction is the result of simple confirmation [29], others suggest that state of neither
satisfaction nor dissatisfaction lead to simple satisfaction [30].
[23] Proposed a model that shows information satisfaction is one of the customer’s satisfaction items. This
model is shown in Figure 2.2.
ISSN: 2289‐1358 P a g e | 4 JOURNAL OF RESEARCH AND INNOVATION IN INFORMATION SYSTEMS http://seminar.utmspace.edu.my/myaisprint/ Figure 2.2: EDT model which present information satisfaction [23]
According to this model of EDT, satisfying customers is not limited to expectation of products or
services. Rather than these factors, satisfying customer from perceived information is the first step that can
attract customer’s trust to offered products and services by business.
If they realize that perceived information of product or service satisfy their initial expectations, then
occurred positive disconfirmation leads to their satisfaction. In versus, if the perceived information of products
or services doesn’t match with their initial satisfaction, then negative disconfirmation leads to their
dissatisfaction.
[7] Divided customer’s demands to two concepts consist of “expectations” and “desires”.
“Expectations” are defined as a set of standards that predict expectations and anticipates of customer about
specific product or service [31,32,33].On the other hand, “desires “are defined as a set of attributes that present
more value to the customers [23]. Figure 2.3 shows the impact of “Expectations” and “desires “on perceived
performance in EDT model.
ISSN: 2289‐1358 P a g e | 5 JOURNAL OF RESEARCH AND INNOVATION IN INFORMATION SYSTEMS http://seminar.utmspace.edu.my/myaisprint/ Figure 2.3: Desires and Expectation Disconfirmation model [7]
According to this model of EDT (Figure 2.3), expectations has a positive impact on perceived
performance [7, 9] and desires produce a positive relationship with perceived performance, too [7]. Also,
Disconfirmation generates a positive effect on overall satisfaction, that is consists of both negative and positive
disconfirmation [9]. Despite of pervious researches that didn’t find any relationship between perceived
performance and overall satisfaction [5,23], current research has confirmed performance has direct impact on
overall satisfaction [23,27,35].Overall e-satisfaction can define as customer’s satisfaction of previous purchase
experience from websites in different aspects such as customer’s information satisfaction, online facilities
satisfaction and purchase satisfaction.
In summary, EDThas two famous variables that are named (expectation or desire) and (experience or
percieved performance). These variables are defined in two different time periods. (Expectation or desire) are
related to the pre-purchase time period that a customer has intial expectaion or desire about a specific
performance such as quality of products or services. (Experience or perceived performance) are related to the
after-purchase time period that the customer gets experience after perceiving a real performance such as quality
of specific product or service. The diferrence between (initial expectation or desire) and (percieved experience
or performance) is known as disconfirmation of expectation or desire [5,7,8].
The result of this difference, means disconfirmation of expectation or desire can be positive or
negative.When customer’s perceived performance about the quality of specific product or service is better than
customer’s expectation or desire,the positive disconfirmation will ocure.At the same way, when customers
perceives the performance worse than what they expected or desired about the quality of specific product or
service,the negative disconfirmation will emerge.According to [9] positive disconfirmation will lead to customer
satisfaction and negative disconfirmation means perceived performance of products or services couldn’t attract
customer satisfaction. These three teorical definitions involve expectations, negative or positive disconfirmation
and customer’s behaivour along satisfaction or dissatisfaction are explained transparently by a framework of
[12] that divided these three kinds of definition to three part and explained the relationship among them.
[12] proposed a conceptual framework consist of three parts: part 1(expectations), part 2 (customer’s
satisfaction or dissatisfaction) and part3 (customer’s behaviors).This framework is illustrated in Figure 2.4. It
clearly shows meeting which kinds of expectation in part 1 lead to customer satisfaction in part 2 and in versus
failure of meeting which kinds of expectations in part 1cause dissatisfaction feel in customers as part 2, also it
indicates satisfaction or dissatisfaction feels as part 2 lead to which behaviors in customers as part 3.
ISSN: 2289‐1358 P a g e | 6 JOURNAL OF RESEARCH AND INNOVATION IN INFORMATION SYSTEMS http://seminar.utmspace.edu.my/myaisprint/ Figure 2.4 Conceptual framework of EDT [12]
First part of this framework indicates that customer’s expectations have different levels consist of two
zones: intolerable and tolerable areas. In intolerable zone, the smallest difference between customer’s
expectation and perceived performance will lead to dissatisfaction result as is shown in part 2, while in tolerable
zone three state is predictable. First, when perceived performance is adequate and acceptable in comparison with
customers expectation that leads to acceptance result of previous usage of product or services in part 2, but it yet
has a negative disconfirmation because couldn’t make a more satisfaction in customers. Second, when perceived
performance is very near to whatever customer had desired or predicted that lead to satisfaction or delight feel.
Disconfirmation of this difference will be positive because this performance could make more satisfaction in
customers.
Third part explains customer behavior from perceived satisfaction or dissatisfaction. High satisfaction or
even delight feel in customers from previous purchase will lead to compliment behavior and as it is predictable
dissatisfaction feel will lead to complain behavior.
2.3 EDT measurement methods
[7] examined five methods for measuring disconfirmation of customer‘s expectation and desire and
identified advantages and disadvantages of these methods. Tables 2.1 till 2.5 explain these methods with details.
ISSN: 2289‐1358 P a g e | 7 JOURNAL OF RESEARCH AND INNOVATION IN INFORMATION SYSTEMS http://seminar.utmspace.edu.my/myaisprint/ Table 2.1: Difference score (DIFF) [7]
Method of
Disconfirmation
Measurement
Difference
score
(DIFF)
Studies
[1,35,36,37,38,39,40,
41]
Description
Mathematical
Verbal
Description
∑(Pi- Si )
where Pi is the
performance on
attribute i;
Si is the standard on
attribute i.
Disconfirmation
is the numerical
difference
between
performance and
a pre experience
Standard.
Advantages: this method is efficient when measures of the standard and performance are needed.
Disadvantages: low reliability, assumes pre use expectations are the same as retrieved expectations.
Table 2.2: Direct effects Model (DEM) [7]
Method of
Disconfirmation
Measurement
Direct effects
Model (DEM)
Studies
[40,42,43]
Description
Mathematical
Verbal Description
∑Pi, ∑Si
where: Pi is the
performance on
attribute i;
Si is the standard
on attribute i.
The standard and
perceived performance
are
modeled as direct
antecedents of
satisfaction.
Advantages: Does not constrain the effects of the standard and performance to be equal, as do difference
scores.
Disadvantages: Assumes pre use expectations are the same as retrieved expectations.
ISSN: 2289‐1358 P a g e | 8 JOURNAL OF RESEARCH AND INNOVATION IN INFORMATION SYSTEMS http://seminar.utmspace.edu.my/myaisprint/ Table 2.3: Better than/worse than model (BTWT) [7]
Method of
Disconfirmation
Measurement
(BTWT)
Better than/
worse than
Studies
[5,27,32,35]
Description
Mathematical
∑SDi where:
SDi is the subjective
judgment of the degree of
difference between
performance and the
standard, and an evaluation
of this difference.
Verbal Description
Disconfirmation is a
subjective assessment
of whether the
performance was
better than or worse
than a standard.
Advantages: Straightforward, direct measure.
Disadvantages: May produce are striction in range when used with desires; past research has found a lack of
relationship with its purported antecedents
Table 2.4: Standard-percept disparity model (SPD) [7]
Method of
Disconfirmation
Measurement
Standard-percept
disparity (SPD)
Studies
[44]
Description
Mathematical
Verbal Description
∑SDi where:
SDi is the subjective
judgment of the degree
of difference between
performance and the
standard.
Disconfirmation is a
subjective
assessment of how
performance is
different from the
standard.
Advantages: Straightforward, direct measure.
ISSN: 2289‐1358 P a g e | 9 JOURNAL OF RESEARCH AND INNOVATION IN INFORMATION SYSTEMS http://seminar.utmspace.edu.my/myaisprint/ Disadvantages: Does not account for performance that exceeds the standard; does not explicitly include an
evaluation of difference.
Table 2.5: Additive Difference model (ADM) [7]
Method of
Disconfirmation
Measurement
Additive
Difference
model (ADM)
Study
[7,45]
Description
Mathematical
Verbal
Description
∑SDi ei where:
SDi is the subjective
judgment of the degree
of difference between
performance and
the standard.
And (ei) is the
evaluation of
this difference.
Disconfirmation is
a subjective
assessment of how
performance is
different from the
standard.
Multiplied by an
evaluation of this
difference.
Advantages: Close match to conceptual definition of disconfirmation; is a general form of other combinatorial
methods.
Disadvantages: Requires two measures for each attribute.
3. METHODOLOGY
This study focuses on a review of EDT to fulfill three objectives of this study. EDT model evolution
reviewed to identify capabilities of EDT in measuring customer satisfaction from multiple aspects. For this aim,
this review started from first model of EDT by [11] and introduced the capabilities which added to the first
model of EDT to measure customer satisfaction from different aspects such as satisfaction of products and
services quality and information quality that provide by specific B2C E-commerce.
For introducing EDT measurement methods, a review on [7] conducted by this study for introducing 5
measurement methods of EDT and their strengths and weaknesses. At the end of this review with comparison
among multiple measurement models, appropriate models that can measure customer satisfaction from all
aspects will introduce in the conclusion of the review.
4. CONCLUSION
[7] examined Five methods which are introduced in the previous part for measuring disconfirmation of
customer‘s expectation and desire. The results showed the only methods that worked well across both standards
involve customer‘s expectation and desire were the Additive Difference Model (ADM) and Direct Effects
Model (DEM). The usefulness of the ADM is primarily in theoretical research where researchers want to use a
common method for measuring both desires disconfirmation and expectations disconfirmation.
ISSN: 2289‐1358 P a g e | 10 JOURNAL OF RESEARCH AND INNOVATION IN INFORMATION SYSTEMS http://seminar.utmspace.edu.my/myaisprint/ Between DEM and ADM methods, when managers need information about desires and expectations
DEM appears to be a good choice but it does not provide a distinct measure of the disconfirmation of customer‘s
expectation and desire. That’s why it is not suitable in most managerial issues because managers can’t realize
their operation in providing customer’s satisfaction. In versus ADM provide a distinct measure of the
disconfirmation of customer‘s expectation and desire. That’s why it is concerned by managerial issues.
Because of the importance of Additive Difference Model (ADM) in measuring disconfirmation of
customer‘s expectation and desire which make possible measuring customer’s satisfaction, in the next section
literature review is followed by studying ADM mathematically to identify how ADM measure customer
satisfaction.
Author believes ADM model can use as an accurate method for measuring customer satisfaction from
quality of services, products and information which present by websites of B2C e-businesses. Also, it can use
for measuring customer satisfaction from actual performance of B2C e-businesses which deliver their products
to the customers non-virtually. Delivery of right products in the right time with the right quality all are some
aspects of customer satisfaction that can meet customer’s expectation and can measure by ADM method
accurately. There is not adequate consider on this method in the previous studies for measuring customer
satisfaction from the applications that displayed above. This review can encourage researchers to use this
method to examine in suggested applications for measuring customer satisfaction.
ACKNOWLEDGMENT
The author knowledge involved of the useful and constructive comments of Dr.Aryati Bt Bakri and Dr.Ab Razak Che
Hussin.
REFERENCES
[1] Zeithaml, V. A., Berry, L. L., & Parasuraman, A. (1996). The behavioral consequences of service quality.
Journal of Marketing 60(2), 31–46.
[2] Brady, M. K., & Cronin, J. J. (2001). Some new thoughts on conceptualizing perceived service quality: A
hierarchical approach. Journal of Marketing, 65(3), 34–49.
[3] Brady, M. K., Knight, G. A., Cronin, J. J., Tomasb, G., Hult, M., & Keillor, B. D. (2005). Removing the
contextual lens: A multinational, multi-setting comparison of service evaluation models. Journal of
Retailing, 81(3), 215–230.
[4] Kalacota, R., & Whinston, A. (1997). Electronic Commerce: A Manager's Guide. Addison-Wesley, Reading,
MA.
[5] Oliver, R. L. (1980a). A cognitive model of the antecedents and consequences of satisfaction decisions.
Journal of Marketing Research, 17(November), 460–469.
[6] Patterson, P., & L. Johnson. (1997). "Modeling the determinants of customer satisfaction for business-tobusiness professional services.". Journal of the Academy of Marketing Science, 25(1), 4-17.
[7] Spreng, R. A., & Jr., T. J. P. (2003). A Test of Alternative Measures of Disconfirmation. Decision Sciences,
34(1).
ISSN: 2289‐1358 P a g e | 11 JOURNAL OF RESEARCH AND INNOVATION IN INFORMATION SYSTEMS http://seminar.utmspace.edu.my/myaisprint/ [8] Bhattacherjee, A., & Premkumar, G. (2004). Understanding changes in belief and attitude toward
information technology usage: A theoretical model and longitudinal test. MIS Quarterly, 28(2), 229254.
[9] Yi, Y. (1990). A critical review of consumer satisfaction. In V. A. Zeithaml (Ed.), Review of marketing 1990.
Chicago: America Marketing Association, 68–123.
[10] Diehl, K. a., & P., C. (2010). "Great Expectations?! Assortment Size, Expectations, and Satisfaction.".
Journal of Marketing Research 47(2), 312-322.
[11] Oliver, R. L. (1977). "Effect of expectation and disconfirmation on postexposure product evaluations: an
alternative interpretation.". Journal of Applied Psychology, 62(4), 480-486.
[12] Santos, J., & Boote, J. (2003). "A theoretical exploration and model of consumer expectations,post
purchase affective states and affective behaviour.". Journal of Consumer Behaviour, 3(2), 142-156.
[13] Fallon, P., & Schofield, P. (2003). "First-timer versus repeat visitor satisfaction: the case of Orlando,
Florida.". Tourism Analysis, 8(2), 205-210.
[14] Gotlieb, J., & B., D. G. (1994). "Consumer satisfaction and perceived quality:Complementary or divergent
constructs?". Journal of Applied Psychology, 79(6), 875.
[15] Bhattacherjee, A. (2001a). An empirical analysis of the antecedents of electronic commerce service continuance. Decision Support Systems, Volume, 32(2), 201-214.
[16] Bhattacherjee, A. (2001b). Understanding information systems continuance:An expectation-confirmation
model. MIS Quarterly Journal of Economics, 25(3), 351-370.
[17] Hsu, M., & H., C. H. Y. (2006). "A longitudinal investigation of continued online shopping behavior: An
extension of the theory of planned behavior.". International Journal of HumanComputer Studies, 64(9),
889-904.
[18] Khalifa, M. L., V. . (2002). Satisfaction with Internetbased services:The role of expectations and desires.
International Journal of Electronic Commerce, 7(2), 31-49.
[19] Patterson, P., & L. Johnson. (1997). "Modeling the determinants of customer satisfaction for business-tobusiness professional services.". Journal of the Academy of Marketing Science, 25(1), 4-17.
[20] Picazo-Vela, S. (2009). The Effect of Online Reviews on Customer Satisfaction: An Expectation
Disconfirmation Approach. AMCIS 2009 Doctoral Consortium.
[21] Chen, C.-F. (2008). Investigating structural relationships between service quality, perceived value,
satisfaction, and behavioral intentions for air passengers: Evidence from Taiwan. Transportation
Research Part A 42, 709–717.
[22] Finn, A., Wang, L., & Frank, T. (2009). Attribute Perceptions, Customer Satisfaction and Intention to
Recommend E-Services. Journal of Interactive Marketing, 23, 209–220.
[23] Spreng, R. A., MacKenzie, S. B., & Olshavsky, R. W. (1996). A reexamination of the determinants of
consumer satisfaction. Journal of Marketing 60, 15-32.
[24] Harmon-Jones, E. H.-J. a. C. (2007). Cognitive Dissonance Theory: An Update with a Focus on the ActionBased Model. Handbook of Motivation Science. J. Y. S. a. W. L. Gardner,The Guilford Press.
[25] Hausknecht, D. J. S. (1998). "" After I Had Made the Decision, I...:" Toward a Scale to Measure Cognitive
Dissonance.". Journal of Consumer Satisfaction Dissatisfaction and Complaining Behavior 119-127.
[26] Staples, D. S., & Wong, I. (2002). Having expectations of information systems benefits that match received
benefits: does it really matter? Information & Management 40(2), 115-131.
[27] Churchill, G. A., & Surprenant, C. (1982). An investigation into the determinants of consumer satisfaction.
Journal of Marketing Research, 19(November), 491–504.
[28] Haistead, D., & Hartman, D. (1994). "Multisource effects on the satisfaction formation process." Journal of
the Academy of Marketing Science, 22(2), 114-129.
[29] Hunt, H. K. (1991). "Consumer satisfaction, dissatisfaction and complaining behavior.". Journal of Social
Issues, 24(1), 107-117.
[30] Erevelles, S., & Leavitt, C. (1992). "A comparison of current models of consumer
satisfaction/dissatisfaction.". Journal of Consumer Satisfaction, Dissatisfaction and Complaining
Behavior, 5(10), 104-114.
[31] Bearden, W. O., & Teel, J. E. (1983). Some determinants of consumer satisfaction and complaint reports.
Journal of Marketing Research 20(February), 21–28.
ISSN: 2289‐1358 P a g e | 12 JOURNAL OF RESEARCH AND INNOVATION IN INFORMATION SYSTEMS http://seminar.utmspace.edu.my/myaisprint/ [32] Cadotte, E. R., Woodruff, R. B., & Jenkins, R. L. (1987). Expectations and norms in models of consumer
satisfaction. Journal of Marketing Research, 24(August), 305–314.
[33] Olson, J. C., & Dover, P. A. (1979). Disconfirmation of consumer expectations through product trial.
Journal of Applied Psychology, 64(2), 179–189.
[34] Anderson, E. W., & Sullivan, M. W. (1993). The antecedents and consequences of customer satisfaction for
firms. Marketing Science, 12(Spring), 125–143.
[35] Tse, D. K., & Wilton, P. C. (1988). Models of consumer satisfaction formation: An extension. Journal of
Marketing Research, 25(May), 204–212.
[36] Swan, J. E., & Trawick, I. F. (1981). Satisfaction explained by desired vs. predictive expectations.In K.
Bernhardt, I. Dolich, M. Etzel, W. Kehoe, W. Perreault,Jr., & K. Roering (Eds.), The changing
marketing environment: New theories and applications. . Educator’s Conference Proceedings. Chicago:
American Marketing Association, 170–173.
[37] Myers, J. H. (1988). Attribute deficiency segmentation: Measuring unmet wants. In Michael J. Houston
(Ed.), Advances in Consumer Research. Vol. 15, Provo, UT: Association for Consumer Research, 108–
113.
[38] Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). Servqual: A multiple item scale for measuring
consumer perceptions of service quality. Journal of Retailing, 64(1), 12–40.
[39] Kettinger, W. J., & Lee, C. C. (1995). Perceived service quality and user satisfaction with the information
services function. Decision Sciences, 25(5), 737–766.
[40] Dabholkar, P. A., Shepherd, C. D., & Thorpe, D. I. (2000). A comprehensive framework for service
quality: An investigation of critical conceptual and measurement issues through a longitudinal study.
Journal of Retailing, 76(2), 139–173.
[41] Jiang, J. J., Klein, G., & Crampton, S. M. (2000). A note on SERVQUAL reliability and validity in
information system service quality measurement. Decision Sciences, 31(Summer), 725–744.
[42] Edwards, J. R. (1994). The study of congruence in organizational behavior research: Critique and a
proposed alternative. Organizational Behavior and Human Decision Processes, 58, 51–100.
[43] Brown, T. J., & Kirmani, A. (1999). The influence of preencounter affect on satisfaction with an anxietyprovoking service encounter. Journal of Service Research Policy, 1(May), 333–346.
[44] Westbrook, R. A., & Reilly, M. D. (1983). Value-percept disparity: An alternative to the disconfirmation of
expectations theory of consumer satisfaction. In R. P. Bagozzi & A. M. Tybout (Eds.), Advances in
consumer research. Vol. 10, Ann Arbor, MI: Association for Consumer Research, 256–261.
[45] Spreng, R. A., & Mackoy, R. D. (1996). An empirical examination of the antecedents of perceived service
quality and satisfaction. Journal of Retailing, 72(2), 201–214.
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